Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods

NeurIPS 2019 Kevin J LiangGuoyin WangYitong LiRicardo HenaoLawrence Carin

We investigate time-dependent data analysis from the perspective of recurrent kernel machines, from which models with hidden units and gated memory cells arise naturally. By considering dynamic gating of the memory cell, a model closely related to the long short-term memory (LSTM) recurrent neural network is derived... (read more)

PDF Abstract

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper